Fault-tolerant control for model-free networked control systems under DoS attacks

This paper studies the fault-tolerant model-free adaptive control (FT-MFAC) problem for a class of single-input single-output (SISO) nonlinear networked control systems (NCSs) under denial-of-service (DoS) attacks. A novel FT-MFAC framework is established with the consideration of DoS attacks and the sensor fault, in which DoS attacks obeying the Bernoulli distribution randomly happen in the sensor-to-controller channel and the sensor fault is approximated by the radial basis function neural network (RBFNN). Based on the proposed framework, an FT-MFAC algorithm that uses only input/output data is proposed to guarantee that the output tracking error is bounded in the sense of mean square. Finally, the effectiveness of the proposed algorithm is illustrated by a simulation. (C) 2021 Published by Elsevier Ltd on behalf of The Franklin Institute.

Automated summary

This paper investigates the FT-MFAC problem for a class of SISO nonlinear NCSs under DoS attacks, presenting a novel framework and algorithm to ensure bounded output tracking error using only input/output data. The effectiveness of the proposed algorithm is demonstrated through simulation.